Objective: This in vitro study is aimed to compare and evaluate the cyclic fatigue of four varying NiTi rotary instrumentation systems. Method: In this study, four types of rotary files were used in four groups (10 files for each group), namely, Group A: Wave One Gold; Group B: AF Blue R3; Group C: One Curve; Group D: F6 SkyTaper. These groups were evaluated by a cyclic fatigue apparatus to measure cyclic fatigue resistance within the artificial metallic simulating canal that has a 60 angle of curvature, the curvature radius was 5 mm, whereas the inner diameter of the canal was 1.5 mm. All the files were rotated in artificial canals until they fracture. The resistance to cyclic fatigue was determined by counting the number of cycles to frac

The current research discusses the topic of the formal data within the methodological framework through defining the research problem, limits and objectives and defining the most important terms mentioned in this research. The theoretical framework in the first section addressed (the concept of the Bauhaus school, the philosophy of the Bauhaus school and the logical bases of this school). The second section dealt with (the most important elements and structural bases of the Bauhaus school) which are considered the most important formal data of this school and their implications on the fabrics and costumes design. The research came up with the most important indicators resulting from the theoretical framework.
Chapter three defined the

Objective: To identify the effectiveness of instruction oriented intervention for primipara women upon episiotomy and self
perineal care.
Methodology: A quasi-experimental study was carried out to determine the effectiveness of instruction-oriented
intervention for primipara women upon episiotomy and self-perineal care. A purposive "non-probability" sample of (60)
primipara mothers was selected from Ibn AL-Balady Pediatric and Maternity Hospital, Al-russafa, Baghdad. The sample
has been divided into two groups; (30) primipara women who were considered as a study group, and another (30) primipara
women who were considered as a control one. The study group was exposed to an instruction-oriented intervention. While,
the

Dye-sensitized solar cells (DSSC) create imitation photosynthesis by using chemical reactions to produce electricity from sunlight. DSSC has been pursued in numerous studies due to its capability to achieve efficiencies of up to 15% with artificial photosensitizer in diffuse light. However, artificial photosensitizers present a limitation because of the complex processing of metal compound. Therefore, various types of sensitizers were developed and synthesized to surpass the artificial sensitizer performances such as natural sensitizers from bio-based materials including plants, due to simple processing techniques and low environmental impact. Thus, this study examines the potential and properties of natural sensitizers from the was

A series of new 4-(((4-(5-(Aryl)-1,3,4-oxadiazol-2-yl)benzyl)oxy)methyl)-2,6-dimethoxy phenol (6a-i) were synthesized from cyclization of 4-(((4-hydroxy-3,5-dimethoxy benzyl)oxy)methyl)benzohydrazide with substituted carboxylic acid in the presences of phosphorusoxy chloride.The resulting compounds were characterized by IR, 1H-NMR, 13C-NMR, and HRMS data. 2,2-Diphenyl-1-picrylhydrazide (DPPH) and ferric reducing antioxidant power (FRAP) assays were used to screen their antioxidant properties. Compounds 6i and 6h exhibited significant antioxidant ability in both assay. Furthermore, type of substituent and their position of the aryl attached 1,3,4-oxadiazole ring at position five are play an important roles in enhancing or declining the antio

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne